Vasodilator stress perfusion CMR is feasible and has prognostic value in morbid obese patients without known CAD

Introduction Obesity is a growing public health problem with an impact on cardiovascular disease. But current methods for the detection of myocardial ischemia remain limited in obese patients and stress cardiac magnetic resonance (CMR) may be a powerful alternative. To determine feasibility and prognostic value of vasodilator stress perfusion CMR in morbid obese patients with body mass index (BMI) ≥ 40 kg/m 2 . Method Consecutive patients with a BMI > 40 kg/m 2 and without known coronary artery disease (CAD) referred for vasodilating stress CMR were followed for major adverse cardiovascular events MACE, defined as cardiac death, non-fatal myocardial infarction of stroke. Univariable and multivariable Cox regressions for MACE were performed to determine the prognostic association of inductible ischemia or late gadolinium enhancement (LGE) by CMR. Results Of 452 obese patients (mean BMI 43.9 ± 3.8 kg/m 2 , 44% of men), 444 (98%) completed the CMR protocol and among those, 404 (91%) completed the follow-up (mean 5.6 ± 2.2 years). Patients without inductible ischemia or LGE experienced a susbtantially lower annual rate of MACE (3.3% vs. 12.4% for those with ischemia and vs. 11,2% for those with ischemia and LGE). In a multivariable stepwise Cox regression including clinical characteristics and CMR indexes, the absence of inducible ischemia was an independent predictor of a lower incidence of MACE at follow-up (Hazard ratio 0.20, 95% confidence interval: 0.11 to 0.36; P Fig. 1 ) and cardiac death (hazard ratio 0.11 95% confidence interval: 0.02 to 0.63). Using Kaplan-Meier analyses, myocardial ischemia identified future CV events/survival ( P Conclusion Stress CMR is feasible and has a high prognostic value in morbid obese patients, with a very low negative event rate in patients without ischemia or infarction as opposed to patients with inducible ischemia and/or presence of myocardial infarct. Kaplan-Meier curves ( Fig. 1 ).